SCG point pick process device and method

ABSTRACT

A seismocardiograph using multiple accelerometer sensors to identify cardiac valve opening and closing times. A methodology for selecting event times is also disclosed.

CROSS REFERENCE TO RELATED CASES

The present application incorporates by reference and claims the benefitof U.S. Provisional Application 60/687,258 filed Jun. 3, 2005 andentitled SCG Point Pick Process and Method.

BACKGROUND OF THE INVENTION

Seismocardiographic (SCG) devices and methods are known in the art. Ingeneral these devices use an accelerometer to monitor the patient'sheart. In use, an accelerometer is placed on the surface of the patientto detect compression waves originating in the patient's heart. Thecompression waves received by the accelerometer are digitized andanalyzed with a computer. These SCG devices may be used for cardiacmonitoring and diagnostic purposes. In some instances the SCG is used asa replacement for electrocardiographic monitoring of heart rate. In thepresent invention the system is used to find time intervals betweenmitral valve opening (MO) and mitral valve closure (MC) times, as wellas the opening time (AO) and closing times (AC) for the aortic valve.The time intervals may be used to compute classic measures of cardiacperformance including the isovolumic contraction time and the leftventricular ejection time (LVET). At the present time such measures aremade with echocardiography.

SUMMARY OF THE INVENTION

The purpose of the point picking process is to determine the aortic andmitral valve timing. A measure for AO, AC and MO, MC timing is sought sothat time interval measurements may be made.

In the present system, several accelerometers are used, preferablythree, in a several locations to accentuate the reception of differentcharacteristics of the cardiac waveform. It is preferred, for example,to use an acceleration sensor on the xyphoid process of the patient onthe midline of the sternum as well as another accelerometer sensor atapproximately the fourth intercostal space on the rib cage. This latterlocation places a sensor over the apex of the heart. In addition it isdesirable to place a third sensor on the carotid artery on the patient'sneck preferably above the bifurcation point where the common carotiddivides into the external carotid and the internal carotid.

In operation, the SCG waveforms of the heart will usually be collectedalong with a conventional electrocardiographic (ECG) tracing. Certainmechanical events are “picked out” based upon a set of rules describedin detail below. In one embodiment the ECG is an integral requirement ofthe point pick process since it provides a fiducial reference to permitaveraging of the SCG waveforms. In an alternate embodiment the SCG isevaluated for cardiac events without reference to the ECG. Either theSCG data is used in “w” form or it may be averaged using the carotidevidence of AO or AC as fiducial points for SCG averaging. This “SCGonly” embodiment eliminates the need for a simultaneous ECG for SCGinterpretation and may be particularly desirable where ECG recoding isdifficult for example in a magnetic resonance imaging magnet.

BRIEF DESCRIPTION OF THE DRAWINGS

Throughout the various figures identical reference numeral indicateidentical structure, wherein;

FIG. 1 is a schematic diagram of the physical system coupled to apatient;

FIG. 2 is a data sequence of simultaneously recorded waveforms from apatient in normal sinus rhythm (NSR) presented in several panels where;

FIG. 2A is a surface ECG tracing;

FIG. 2B is an SCG tracing a xyphoid sensor on the rib cage;

FIG. 2C is an SCG tracing from an apical sensor on the rib cage;

FIG. 2D is an SCG tracing from a carotid sensor on the neck over thecommon carotid at about the bifurcation;

FIG. 3 is data from a patient in normal sinus rhythm (NSR) in two panelswhere;

FIG. 3A is an event analysis presentation for a mechanical cardiacevents of a patient's heart in NSR;

FIG. 3B is a tracing showing two SCG wavelets taken from a patient inNSR;

FIG. 4 is data from a carotid sensor on a patient in NSR in two panelswhere;

FIG. 4A is an event analysis presentation for mechanical cardiac eventsof a patient's heart in NSR;

FIG. 4B is single carotid tracing of a patients heart in NSR;

FIG. 5 is data from a patient in an atrial paced rhythm (AAI) in severalpanels where;

FIG. 5A is a surface ECG tracing;

FIG. 5B is an SCG tracing from a xyphoid sensor on the rib cage;

FIG. 5C is an SCG tracing from an apical sensor on the rib cage;

FIG. 5D is an SCG tracing from a carotid sensor on the neck over thecommon carotid;

FIG. 6 is data from a patient in a ventricular paced rhythm (VVI) inseveral panels where;

FIG. 6A is a surface ECG tracing;

FIG. 6B is an SCG tracing from a xyphoid sensor on the rib cage;

FIG. 6C is an SCG tracing from an apical sensor on the rib cage;

FIG. 6D is an SCG tracing from a carotid sensor on the neck over thecommon carotid;

DETAILED DESCRIPTION OF AN ILLUSTRATIVE EMBODIMENT

Overview

The objective of the method and device is to extract the “time” thatcertain cardiac events occur during the heart rhythm of a patient. Inthe heart a single heart contraction pumps blood and the sequence ofmechanical events proceeds from mitral valve closure (MC) to aorticvalve opening (AO). Next the aortic valve closes (AC) followed by mitralvalve opening (MO). This sequence of cardiac valve actuation eventsresults in the ejection of blood in to the aorta and the lungs. Theopening and closing of valves give rise to the compression wavesinterpreted by the invention. These same mechanical events are caused bythe contraction of the muscles in the heart which gives rise to anindependent electrographic waveform (ECG) measured on the surface of thepatient's body. Knowledge of the time intervals between these mechanicalcardiac events and the electrographic counterpart events has substantialdiagnostic value and any of several measures of cardiac performance maybe computed from the time intervals.

Hardware Implementation

In the illustrative embodiment of the system, multiple channels ofaccelerometry are used and in the current design each channel isidentical in terms of electrical performance. It is expected thatcertain optimization may be used to tailor the channels to theirrespective signals within the scope of the invention. The preferredlocations are identified in the description but alternates sites may beequivalent in terms of function.

In use the several sensors are placed on the patient 16 to pick updifferent cardiac characteristics of a simultaneously recorded signals.That is, all the data is time stamped or aligned in time so that thepoint pick measurement process may move from one waveform to the other.The waveform figures are displayed as panels to show this feature. Asshown in FIG. 1, it is preferred, for example, to use both anacceleration sensor on the xyphoid process 10 of the patient on themidline of the sternum as well as at approximately the fourthintercostals space on the rib cage corresponding to the apex 12 of theheart. In addition a third sensor 14 should be placed on the carotidartery preferably above the bifurcation point where the common carotiddivides. Multiple electrode typified by electrode 18 are placed in aconventional “lead 12” pattern on the patient to pick up and record theECG.

The accelerometers are identical and they may be piezoelectric deviceswith a frequency response for DC to 20,000 HZ generating approximately1000 mv/G. The high impedance sensors generate signals that aredelivered to the interface 20 via shielded cables. Commerciallyavailable sensor may weigh as little as 20 grams which facilitates theirplacement on the body. The signal processing for the accelerometersignals of the three sensors is similar and the signal processing andanalog to digital conversion occurs in a companion interface 20. Theinvention has been implemented with the commonly available “Lab View”hardware platform manufactured by National Instruments Co. The SCGaccelerometer signals are buffered and bandpass amplified with a flatfilter having corner frequencies of approximately 0.3 Hz and 170 Hz.After filtration the signals are digitized with an A to D converter witha sampling rate of about 1K sps, and presented to the computer 21 whichuses software to analyze the signals from the ECG and the SCGaccelerometers. A user selectable interpretation recording is made ofbetween about 3 to 15 seconds of data covering several beats. A moving3-15 second window of data is recorded and is available for processing.Longer and shorter windows are operable.

Experimentation suggests that the system of the invention is quitetolerant of the signal processing methodology. Since implementation isreadily carried out with “off the shelf” hardware the hardwareimplementation is not described in more detail.

SCG Point Pick Process

In most of the examples and during cardiac testing, the various SCGwaveforms of the heart are collected along with a simultaneousconventional ECG tracing. The recordings are all taken simultaneouslyand the time relationship between the various waveforms or data sets ispreserved. The SCG waveform is considered and processed as “wavelets”each wavelet is intended to encompass the time interval of a singleheartbeat. Wavelets may be averaged or used individually (raw). Afiducial point for averaging SCG waveforms may be used to expand orcontract the wavelet waveform to permit simple averaging of amplitudevalues. This fiducial point may be taken from the ECG channel where theelectrocardiographic “R-wave” can be extracted from the ECG channel andused to scale and align the SCG waveforms. As an alternative the carotidSCG channel may be taken as indicative for certain events such as AO andAC. These mechanical events can be used scale and then average the SCGdata. In general the averaging process expands or compresses thewavelets until they exhibit the same R-R interval. The averaging processis best achieved by manipulating the data by scaling the data so that itexhibits the same R-R interval and then making an arithmetic average ofcontiguous data sets at the same apparent heart rate. This forced rateensures that mechanical motion events that are averaged at the same“time” in the cardiac cycle. It appears that the best performance isachieved when approximately 3-5 beats of data for each channel are takenand the data in each channel is averaged.

SCG Point Pick Process Schema Table

This table represents the software process carried out by the computer21 described in prose rather than a flow chart. This process is used tocreate the event analysis presentation seen as panel FIG. 3A and FIG.4A, which can be viewed on a computer display screen. Wavelet orwaveform averaging using the simultaneous ECG recording is described inmore details in U.S. Pat. Nos. 4,989,611 and 5,159,932. The processdescribed in the patent is similar channel for channel to the presentimplementation.

1. Point Pick Process with Simultaneous ECG

A multiple channel ECG is collected from the patient to help with theevaluation of the SCG data. In general a lead “III” ECG waveform issufficient and in this ECG channel there should be very distinct QRScomplexes. Only a short interval of data needs to be collected with thepresent system. It has been determined that approximately 3 to 15seconds of data is sufficient to carry out the invention. Theelectrocardiogram (ECG) is analyzed and conventional algorithms are usedto determine the QRS onset as well as the peak of the R-wave. In FIG. 2Athe magnitude and rise time of the waveform has resulted in thedetection and declaration of event 100 and 102 as the “R-wave” in therespective complexes and the companion waveforms of FIG. 2. Rhythmanalysis is provided to remove abnormal beats and in the instance ofpatients having a pacemaker, the pacemaker spike is used as the onset ofthe R-wave an example of this is seen in FIG. 6A where events 104 andevent 106 represent the declaration of the onset of the “R-wave” in thewaveforms of FIG. 6. In the ECG channel the system calculates theaverage standard deviation in medium R to R intervals of the heart tocalculate the heart rate. The simultaneously recorded SCG data isevaluated by establishing an analysis window whose size is determined bythe P to R interval and the R to R interval. The analysis window is theP to R to R interval of the average heartbeat. This window is applied tothe ECG data as well as the simultaneously recorded SCG xyphoid, SCGapex and SCG carotid data. Once the R peaks are aligned a set ofwavelets is created for each of the ECG channels. It is usually requiredto adjust the DC offset for the wavelet and every wavelet is integratedinto a set of velocity wavelets. The velocity wavelets are used as abaseline and they are adjusted to remove noise. Next each velocitywavelet is integrated and a set of displacement wavelets are created.The displacement wavelets are baseline adjusted and any time dependantramping behavior is removed as well.

FIG. 3B shows two overlapping SCG waveforms from the carotid sensor on apatient in NSR. Wavelet 120 and wavelet 122 differ in detail even whenaligned to the same “R-wave” as a fiducial reference. It has been foundthat averaging 3-5 beats greatly reduces the scatter in the event timesshown in FIG. 3A. Although the wavelet disparity seen in FIG. 3B can beimproved by averaging the beats around the electrographic R-wave anotherapproach is available as well.

The distinct inflections seen as 124 and peak 126 seen in FIG. 4Bcorrespond to AO and AC mechanical events. These peaks are very distinctin the carotid waveforms presented in FIG. 4. In this instance thepoints may be selected using an “R-wave” like algorithm that looks atrise time dV/dT and Maximum value to declare the AO and AC events. Onemay use the AO and AC event to carry out averaging in the remaining SCGchannels or they may be applied directly to the raw data in thecompanion waveforms. In this instance the remaining SCG point pickprocesses process maybe run in essentially real time without waveformaveraging. With the SCG wavelets prepared the point picking process isapplied. The process described in the patent is similar channel forchannel to the present implementation.

The point picking process begins with the identification of aorticopening AO and proceeds sequentially to detect the MC, AC and MO events.With reference to the figures the process occurs according to thefollowing rules and procedures.

AO Process

Using the Average Carotid Acceleration Wavelet

-   Process 400 on FIG. 2D corresponds to:

Identify the largest positive peak within 220 msec of the R peak seereference numeral 402;

-   -   Mark this point as AO carotid, see reference numeral 404;    -   If no positive peak is found, start search again at R peak and        search ahead for largest negative peak. When found, search back        for 1^(st) negative knee (concave down), mark this point AO        carotid.        Using the Average Xyphoid Acceleration Wavelet

-   Process 450 on FIG. 2B corresponds to:    -   Starting at AO carotid time, search back 60 msec for largest        positive peak illustrated by arrows 451 and 452 which delimit        the short time interval.    -   Mark this point as AO xyphoid seen at reference numeral 454.        Using the Average Apex Acceleration Wavelet

-   Process 460 on FIG. 2C corresponds to:    -   Starting at AO carotid time, search back 60 msec for largest        negative peak    -   Mark this point as AO apex as shown by reference numeral 462.

-   If _AO xyphoid−AO apex_(—)<=10 msec;

Select AO apex as aortic valve opening AO.

-   If (AO xyphoid−AO apex)>=0 and _AO xyphoid−AO apex_(—)>10 msec;

Select AO xyphoid as pulmonic valve opening PO.

Select AO apex as aortic valve opening AO.

-   If (AO xyphoid−AO apex)<0 and _AO xyphoid−AO apex_(—)>10 msec;

Select AO xyphoid as aortic opening AO.

MC Process

Using the Average Xyphoid Acceleration Wavelet

-   Process 420 on FIG. 2B corresponds to:    -   Start search at AO xyphoid time−10 msec and search back 85 msec        for the largest negative peak, see reference numeral 424.    -   Continue search back from this negative peak 30 msecs for 1^(st)        negative knee.    -   Mark this point MC xyphoid see reference numeral 422.    -   If negative knee not found restart search at negative peak and        search back for 45 msec to find 1^(st) positive peak.    -   Mark this point MC xyphoid        Using the Average Apex Acceleration Wavelet-   Process 430 on FIG. 2C corresponds to:    -   Start search at AO apex time−10 msec and search back 100 msec        for the largest negative peak, see reference numeral 432.    -   Continue search back from this negative peak 30 msecs for 1^(st)        negative knee.    -   Mark this point MC apex as indicated by reference numeral 432.    -   If negative knee not found restart search at negative peak back        for 45 msec to find 1^(st) positive peak.    -   Mark this point MC apex-   If _MC xyphoid−MC apex_(—)<=10 msec;

Select earlier of MC apex or MC xyphoid as mitral valve closure MC.

-   If _MC xyphoid−MC apex_(—)>10 msec and (MC xyphoid−MC apex)>0;

Select MC xyphoid as tricuspid valve closure TC.

Select MC apex as mitral valve closure MC.

-   If (MC xyphoid−MC apex)<0;

Select MC apex as mitral valve closure MC.

AC Process

-   Process 440 on FIG. 2D corresponds to:    Using the Average Carotid Acceleration Wavelet-   Process 440 on FIG. 2D corresponds to:    -   Starting at AO carotid time+200 msec, search ahead for 500 msec        for largest positive peak see reference numeral 442.    -   Mark this point as AC carotid see reference numeral 444.        Using the Average Xyphoid Acceleration Wavelet-   Process 460 on FIG. 2B corresponds to:    -   Start search AC carotid time−15 msec and search back 50 msec for        the 1st negative peak    -   Continue search back from this negative peak 20 msecs for 1^(st)        negative knee.    -   Mark this point AC xyphoid as shown by reference numeral 462.    -   If negative knee not found restart search at negative peak and        search back for 20 msec to find 1^(st) positive peak.    -   Mark this point AC xyphoid        Using the Average Apex Acceleration Wavelet-   Process 470 on FIG. 2C corresponds to:    -   Start search at AC carotid time−15 msec and search back 50 msec        for the 1st positive peak,    -   Continue search back from this positive peak 20 msecs for 1^(st)        positive knee.    -   Mark this point AC apex    -   If positive knee not found restart search at positive peak and        search back for 30 msec to find zero crossing.    -   Mark this point AC apex-   If _AC xyphoid−AC apex_(—)<=10 msec;

Select earlier of AC apex or AC xyphoid as aortic valve closure AC.

-   If _AC xyphoid−AC apex_(—)>10 msec and (AC apex−AC xyphoid)>0;

Select AC xyphoid as tricuspid valve closure TC.

Select AC apex as aortic valve closure AC.

-   If _AC xyphoid−AC apex_(—)>10 msec and (AC apex−AC xyphoid)<0;

Select AC apex as aortic valve closure AC.

MO Process

Using the Average Xyphoid Velocity Wavelet

-   Process 480 on FIG. 2B corresponds to:    -   Start search at AC carotid time+50 msec and search ahead 150        msec for the largest negative peak,    -   Go to corresponding time point on the average xyphoid        acceleration wavelet and search back 75 msec for the 1^(st)        positive knee,    -   Mark this point MO xyphoid as indicated by reference numeral        482.        Using the Average Apex Velocity Wavelet-   Process 490 on FIG. 2C corresponds to:    -   Start search at AC carotid time+50 msec and search ahead 150        msec for the largest negative peak see reference numeral 492,    -   Go to corresponding time point on the average apex acceleration        wavelet and search back 75 msec for the 1^(st) positive knee,    -   Mark this point MO apex see reference numeral 494,    -   Select the later of MO apex and MO xyphoid as mitral valve        opening MO.        II. Point Pick Process without ECG

Point Pick process using AO peak identified in the SCG carotid trace fora fiducial point. The process of picking the AO peak in the carotidtrace is essentially the same as QRS detector; setting threshold levelsfor noise and signal, setting refractory times for AO peak recurrence,and determining AO-AO interval. The AO peak will be used as fiducialmarker for wave alignment and the wavelet window is equal to 0.35*avgAO-AO interval+AO-AO interval.

AO Process

Using the Average Xyphoid Acceleration Wavelet

-   -   Starting at AO carotid time, search back 60 msec for largest        positive peak.    -   Mark this point as AO xyphoid        Using the Average Apex Acceleration Wavelet    -   Starting at AO carotid time, search back 60 msec for largest        negative peak.    -   Mark this point as AO apex

-   If _AO xyphoid−AO apex_(—)<=10 msec;

Select AO apex as aortic valve opening AO.

-   If (AO xyphoid−AO apex)>=0 and _AO xyphoid−AO apex_(—)>10 msec;

Select AO xyphoid as pulmonic valve opening PO.

Select AO apex as aortic valve opening AO.

-   If (AO xyphoid−AO apex)<0 and _AO xyphoid−AO apex_(—)>10 msec;

Select AO xyphoid as aortic opening AO.

MC Process

Using the Average Xyphoid Acceleration Wavelet

-   -   Start search at AO xyphoid time−10 msec and search back 85 msec        for the largest negative peak    -   Continue search back from this negative peak 30 msecs for 1^(st)        negative knee.    -   Mark this point MC xyphoid    -   If negative knee not found restart search at negative peak and        search back for 45 msec to find 1^(st) positive peak.    -   Mark this point MC xyphoid        Using the Average Apex Acceleration Wavelet    -   Start search at AO apex time−10 msec and search back 100 msec        for the largest negative peak    -   Continue search back from this negative peak 30 msecs for 1^(st)        negative knee.    -   Mark this point MC apex    -   If negative knee not found restart search at negative peak back        for 45 msec to find 1^(st) positive peak.    -   Mark this point MC apex

-   If _MC xyphoid−MC apex_(—)<=10 msec;

Select earlier of MC apex or MC xyphoid as mitral valve closure MC.

-   If _MC xyphoid−MC apex_(—)>10 msec and (MC xyphoid−MC apex)>0;

Select MC xyphoid as tricuspid valve closure TC.

Select MC apex as mitral valve closure MC.

-   If (MC xyphoid−MC apex)<0;

Select MC apex as mitral valve closure MC.

AC Process

Using the Average Carotid Acceleration Wavelet

-   -   Starting at AO carotid time+200 msec, search ahead for 500 msec        for largest positive peak.    -   Mark this point as AC carotid.        Using the Average Xyphoid Acceleration Wavelet    -   Start search AC carotid time−15 msec and search back 50 msec for        the 1st negative peak    -   Continue search back from this negative peak 20 msecs for 1^(st)        negative knee.    -   Mark this point AC xyphoid    -   If negative knee not found restart search at negative peak and        search back for 20 msec to find 1^(st) positive peak.    -   Mark this point AC xyphoid        Using the Average Apex Acceleration Wavelet    -   Start search at AC carotid time−15 msec and search back 50 msec        for the 1st positive peak    -   Continue search back from this positive peak 20 msecs for 1^(st)        positive knee.    -   Mark this point AC apex    -   If positive knee not found restart search at positive peak and        search back for 30 msec to find zero crossing.    -   Mark this point AC apex

-   If _AC xyphoid−AC apex_(—)<=10 msec;

Select earlier of AC apex or AC xyphoid as aortic valve closure AC.

-   If _AC xyphoid−AC apex_(—)>10 msec and (AC apex−AC xyphoid)>0;

Select AC xyphoid as tricuspid valve closure TC.

Select AC apex as aortic valve closure AC.

-   If _AC xyphoid−AC apex_(—)>10 msec and (AC apex−AC xyphoid)<0;

Select AC apex as aortic valve closure AC.

MO Process

Using the Average Xyphoid Velocity Wavelet

-   -   Start search at AC carotid time+50 msec and search ahead 150        msec for the largest negative peak    -   Go to corresponding time point on the average xyphoid        acceleration wavelet and search back 75 msec for the 1^(st)        positive knee    -   Mark this point MO xyphoid        Using the Average Apex Velocity Wavelet    -   Start search at AC carotid time+50 msec and search ahead 150        msec for the largest negative peak    -   Go to corresponding time point on the average apex acceleration        wavelet and search back 75 msec for the 1^(st) positive knee    -   Mark this point MO apex    -   Select the later of MO apex and MO xyphoid as mitral valve        opening MO        It should be apparent that many alternative modifications can be        made to the invention without departing from the scope of the        appended claims.

1. A device for monitoring and displaying cardiac function of apatient's heart said heart exhibiting a mitral valve closure MC event, amitral valve opening MO event, an aortic valve closure AC event and anaortic valve opening AO event comprising: a) at least two accelerometersensors placed on the patients body at two locations selected from theset of on the ribcage at the intercostal space over the apex of theheart establishing an apex channel, on the sternum of the patientestablishing a xyphoid channel, on the neck over the location of thecarotid artery establishing a carotid channel; said sensors generatingsignals in response to compression waves originating the heart; b)signal processing system coupled to said sensors for generating anseismocardiographic (SCG) waveform from each of said sensors, and forrecording and storing a segment of said SCG waveform for analysis; c) amodule for a stepwise process for extracting the time of mechanicalevents is selected from the group comprising MC, MO, AC, AO, in theheart from said SCG waveform segment and for presenting the time of eachsuch events to a system user on a display; and d) a set of ECGelectrodes placed on said patient's body for generating signals inresponse to electrical depolarization of originating the heart; e)signal processing system coupled to said ECG electrodes for generatingan ECG waveform, and for recording and storing a segment of said ECGwaveform for analysis; f) a module for an AO selection process in oneSCG channel from one of said sensors, wherein the process includes:forming an average carotid acceleration wavelet from said carotid SCGchannel waveform; identify the R wave peak in the ECG channel; identifythe largest positive peak in said SCG channel waveform within 220 msecof the R peak and mark this point as AO carotid, if no positive peak isfound, start search again at R wave peak and search ahead for thelargest negative peak, when found, search back for the first negativeknee (concave down), and mark this point as AO carotid.
 2. The device ofclaim 1 further comprising; said module for the AO selection process inone SCG channel further wherein the process includes; forming an averagexyphoid acceleration wavelet from said xyphoid SCG channel waveform;starting at AO carotid time, search back 60 msec for largest positivepeak, and mark this point as AO xyphoid.
 3. The device of claim 2further comprising; said module for the AO selection process in one SCGchannel further wherein the process includes; forming an average apexacceleration wavelet from said apex SCG channel waveform; starting at AOcarotid time, search back 60 msec for largest negative peak, and markthis point as AO apex; and if _AO xyphoid−AO apex_(—)=10 msec; thenselect AO apex as aortic valve opening AO; and if (AO xyphoid−AOapex)>=0 and _AO xyphoid−AO apex_(—)>10 msec; select AO xyphoid aspulmonic valve opening PC), and select AO apex as aortic valve openingAO; and if (AO xyphoid−AO apex) 0 and _AO xyphoid−AO apex_(—)>10 msec;then select AO xyphoid as aortic opening AO.
 4. The device of claim 3further comprising; a module for an MC selection process in one SCGchannel, wherein the process includes: forming an average xyphoidacceleration wavelet from said xyphoid SCG channel waveform; startsearch at AO xyphoid time −10 msec and search back 85 msec for thelargest negative peak; continue search back from this negative peak 30msecs for 1st negative knee; and mark this point MC xyphoid; however, ifa negative knee is not found restart search at negative peak and searchback for 45 msec to find 1st positive peak: and mark this point MCxyphoid.
 5. The device of claim 4 further comprising; said module forthe MC selection process in one SCG channel further wherein the processincludes; forming an average apex acceleration wavelet from said apexSCG channel waveform; start search at AO apex time −10 msec and searchback 100 msec for the largest negative peak; and, continue to searchback from this negative peak 30 msecs for first negative knee; and markthis point MC apex; however if a negative knee is not found restartsearch at negative peak back for 45 msec to find first positive peak;then mark this point MC apex; if _MC xyphoid−MC apex_(—)=10 msec; thenselect earlier of MC apex or MC xyphoid as mitral valve closure MC; and,if _MC xyphoid−MC apex_(—)>10 msec and (MC xyphoid−MC apex)>0; then,select MC xyphoid as tricuspid valve closure TC and select MC apex asmitral valve closure MC; however, if (MC xyphoid−MC apex) 0; then selectMC apex as mitral valve closure MC.
 6. The device of claim 1 furthercomprising; a module for an AC selection process in one SCG channel,wherein the process includes: forming an average carotid accelerationwavelet from said carotid SCG channel waveform; starting at AO carotidtime +200 msec, search ahead for 500 msec for largest positive peak;and, mark this point as AC carotid.
 7. The device of claim 6 furthercomprising; said module for the AC selection process in one SCG channelfurther wherein the process includes; forming an average xyphoidacceleration wavelet from said xyphoid SCG channel waveform; startsearch AC carotid time −15 msec and search back 50 msec for the 1stnegative peak; continue search back from this negative peak 20 msecs for1st negative knee mark this point AC xyphoid; if negative knee not foundrestart search at negative peak and search back for 20 msec to find 1stpositive peak, then, mark this point AC xyphoid.
 8. The device of claim7 further comprising; said module for the AC selection process in oneSCG channel further wherein the process includes; forming an averageapex acceleration wavelet from said apex SCG channel waveform; startsearch at AC carotid time −15 msec and search back 50 msec for the 1stpositive peak continue search back from this positive peak 20 msecs for1st positive knee, mark this point AC apex if positive knee not foundrestart search at positive peak and search back for 30 msec to find zerocrossing, then, mark this point AC apex; and, if _AC xyphoid−ACapex_(—)=10 msec; then, select earlier of AC apex or AC xyphoid asaortic valve closure AC; and, if _AC xyphoid−AC apex_(—)>10 msec and (ACapex−AC xyphoid) >0; and, select AC xyphoid as tricuspid valve closureTC, and, select AC apex as aortic valve closure AC; and, if _ACxyphoid−AC apex _(—)10 msec and (AC apex−AC xyphoid) 0; then, select ACapex as aortic valve closure AC.
 9. The device of claim 6 furthercomprising; a module for an MO selection process in one SCG channel,wherein the process includes: forming an average xyphoid accelerationwavelet from said xyphoid SCG channel waveform; start search at ACcarotid time +50 msec and search ahead 150 msec for the largest negativepeak, then, go to corresponding time point on the average xyphoidacceleration wavelet and search back 75 msec for the 1st positive kneeand, mark this point MO xyphoid.
 10. The device of claim 9 furthercomprising; said module for the MO selection process in one SCG channelfurther wherein the process includes; forming an average apexacceleration wavelet from said apex SCG channel waveform; start searchat AC carotid time +50 msec and search ahead 150 msec for the largestnegative peak; go to corresponding time point on the average apexacceleration wavelet and search back 75 msec for the 1st positive knee;mark this point MO apex; select the later of MO apex and MO xyphoid asmitral valve opening MO.